Post-exercise hormone secretion will, per the research today, not predict gains. Even if the hormones secreted are anabolic.

Designing training programs around testosterone maximization and cortisol minimization is most likely not a sound way to do programming.

Intramuscular IGF-1 might be related to gains if measured properly.

Introduction to hormones

Our body uses hormones for sending “slow” long-range signals. Hormones act systemically, meaning they affect the body as a whole. This is in contrast to short-distance cell communication (Tortora & Derrickson, 2012). You have probably heard of hormones like cortisol and testosterone and associate these hormones with stress and growth, respectively.

In my experience, people commonly believe these hormones function in an independent, linear fashion. Meaning more testosterone equals more masculinity and growth, while more cortisol equals stress and catabolism. However, this point of view ignores the fact that hormones have a physiological range where they help the body function optimally (Tortora & Derrickson, 2012). By trying to minimise or maximise certain hormonal responses we ignore the whole-body context in which they exist. Indeed, hormones have many functions. For example, testosterone is a regulator of mental health (Celec et al., 2015). Trying to shoehorn a hormone into one role is overly reductionistic. We all know about hormones like insulin, growth hormone, adrenaline, and cortisol. We probably also have a general idea of their purpose in the body. But were you also aware that these hormones are linked to sleep regulation (McGinnis & Young., 2016)? People who inject hormones like insulin, GH, testosterone, etc. might be inadvertently altering organ functionality in their bodies. This could lead to unwanted and unintended consequences which could be detrimental to their overall health (Lamb, 1984; ACSM, 1987; Su et al., 1993; Sullivan et al., 1998; Hartgens & Kuipers, 2004; Maravelias et al., 2005; Achar et al., 2010; Piacentino et al., 2015; Frati et al., 2015; Grönbladh et al., 2016).

Trying to min-max your hormones like the stats of an RPG character is probably not a good idea given that hormones are essential regulators of homeostasis. By interfering with their natural balance you change a ton of homeostatic parameters, causing butterfly effects. But this review isn’t about the effects of steroids, so let’s get back on topic.

Research now shows that different, and perhaps unexpected, types of tissues can secrete hormones. For example, fat tissue can secrete inflammatory products 1 and hormones 2. In addition to fat, muscle tissue can secrete beneficial hormones (Egan and Zierath, 2013) called myokines 3. This means that muscles and fat can communicate messages to the whole body.

[expand title=”1“][themify_icon icon=”fa-quote-left”] Obesity is characterized by a state of mild inflammation, and [inflammation] generally rises as adipose tissue expands (Trayhurn, 2005)[/expand] [expand title=”2“][themify_icon icon=”fa-quote-left”] The fat surrounding the liver and other abdominal organs, so-called visceral fat, is very metabolically active. It releases fatty acids, inflammatory agents, and hormones that ultimately lead to higher LDL cholesterol, triglycerides, blood glucose, and blood pressure (The Harvard School of Public Health)[/expand] [expand title=”3“][themify_icon icon=”fa-quote-left”] Myokines have been suggested to mediate anti-inflammatory and metabolic effects (…) It is possible that myokines contribute to mediate the preventive effects of exercise against chronic diseases, such as cardiovascular diseases, type 2 diabetes, cancer, and dementia (Karstoft & Pedersen, 2016)[/expand]

[expand title=”Fink et al., (2016) quote about hormones and hypertrophy”][themify_icon icon=”fa-quote-left”]Our findings are in line with a recent study showing no correlation between acute systemic hormonal elevations and muscle hypertrophy (Morton et al. , 2016). Furthermore, a recent study recorded inferior myofibrillar protein synthesis in a RT protocol triggering acute hormonal elevations as compared to a protocol in which hormonal levels did not increase (McKendry et al. , 2016). Indeed, according to previous findings, the hypertrophic effects of GH are strongly regulated by IGF-1 which can be triggered by GH elevations (Cameron et al. , 1988; Goldspink, 1999). Acute local IGF-1 increases in muscle tissue have been shown to be correlated to muscle fibre area increase (Suetta et al. , 2010). However, systemic GH alone does not appear to be directly related to muscle hypertrophy but rather exerts its influence by regulating fat and carbohydrate metabolism (Gravholt et al. , 1999). Further, it is important to make the difference between acute endogenous hormonal elevations and chronic supraphysiological hormonal levels (Bhasin et al. , 1996; Ehrn- borg et al. , 2005). We suggest that the small acute endogenous increases in hormones cannot imitate the anabolic effects of high chronic supraphysiological hormonal levels. Nevertheless, even though acute GH elevations cannot be directly related to muscle hypertrophy, acute GH elevations may be used as metabolic stress marker (Goto et al. , 2005).[themify_icon icon=”fa-quote-left”] [/expand]

Several of the authors agree that local mechanisms are more important than systemic mechanisms 4. Others say there is not enough evidence to make conclusive statements about hormonal changes and gains (Schoenfeld, 2013; Kraemer et al., 2016). Schoenfeld speculates that “the purpose of post-exercise hormonal elevations is to mobilize fuel stores rather than promote tissue anabolism”, which is a hypothesis that fits with AMPK and the “energy crisis of the cell”. Additionally, Schoenfeld presents us with the idea that our genetics determine whether we respond to post-exercise increases in anabolic hormones 5. It’s possible that some people are genetically hardwired to react favourably with endogenous anabolic hormones, while others won’t.

[expand title=”4“][themify_icon icon=”fa-quote-left”] Intramuscular rather than systemic processes [mediate] hypertrophy (Mitchell et al., 2013)[/expand] [expand title=”5“][themify_icon icon=”fa-quote-left”] It has been estimated that genetic differences can account for approximately half of the variation in athletic performance. This is consistent with studies showing that the hypertrophic response to resistance training displays tremendous variance between individuals. It is therefore conceivable that acute hormonal responses may be more relevant to certain lifters as opposed to others. There is some evidence to support this contention as a strong trend for a significant association has been shown between IGF-1 and those who respond favorably to hypertrophy-type training (Schoenfeld, 2013)[/expand]

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A very recent study challenges these arguments, because it finds that acute post-exercise testosterone secretion is related to hypertrophy in 26 resistance trained men over an 8 week training period (Mangine et al., 2016). The authors criticize some of the aforementioned studies because some of them were underpowered (i.e. too few participants) and because they used non-optimal statistical procedures. These are valid arguments. However, I get a bit suspicious when Mangine et al. imply that the research is biased or erroneous 6. This is a bit odd since such a critique could apply to pretty much every study out there. There’s always the possibility of bias and error. If bias and error were present in the hormone studies, they would be interfering with the efforts of several independent research teams. Mangine et al’s findings are very interesting but until they are replicated and supported by other studies, we have to slow-pedal their conclusions.

[expand title=”6“][themify_icon icon=”fa-quote-left”] The validity of this [research] is based upon the assumption that the related variables were collected without systematic or random error (…) data were collected or analyzed using procedures that were dependent upon technician reliability and were therefore subject to error (Mangine et al., 2016)[/expand]

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Beyond hypertrophy, there are studies that suggest there is a link between testosterone secretion and strength gains (Beaven et al., 2008). Though the focus of this article is hypertrophy and not strength, so I won’t go in-depth on this.

Insulin

Atherton and Smith have described insulin as an anti-catabolic hormone that lowers MPB and thus “protects” the body from muscle wasting. Insulin could act synergistically with essential amino acids (EAA), where insulin decreases MPB while EAAs increase MPS (Atherton and Smith, 2012; Everman et al., 2016).

Many studies have measured post-exercise insulin concentrations, and haven’t found any connection to gains. However, their results might be affected by the fact that insulin responds strongly to protein and carbohydrates. In fact, insulin concentrations actually decrease (Schwarz et al., 2011; Mangine et al., 2015) or remain unchanged (Marliss et al., 2002) during exercise. So it makes little sense that insulin would predict hypertrophy when measured right after exercise. But, if exercise was combined with feeding, it’s possible insulin might be correlated with gains.

Insulin secretion is therefore part of the nutrient timing hypothesis which states that consuming carbohydrates and protein around the the exercise window (before, during, after), could lead to improved gains (Kerksick et al., 2008). This hypothesis has been thoroughly researched in the last twenty years. I will write a separate nutrient timing article on this topic specifically.

Can local hormones predict hypertrophy after exercise?

Local hormones can also be described as intramuscular hormones. They exist in contrast to circulating hormones which flow freely in the bloodstream. Some authors think local hormonal concentrations are better at predicting gains compared to circulating hormones.

Conclusion

As per the research presented in this article, there’s little reason to believe temporary changes in hormonal secretion predicts gains. Future research is needed to confirm or deny the hormone hypothesis.

[expand title=”Limitations“]

Given that this is not a peer-reviewed systematic review or meta-analysis, this article is inherently at risk of study selection bias. I always write these reviews/opinions in the state of mind of an open-minded learner, but I can’t exclude the possibility of bias when selecting, interpreting, or discussing these studies. In fact, I would argue that I most likely am biased, as we all are. Furthermore, I do not have the time to represent the literature in its entirety nor evaluate the quality of every study in detail. This means that some of the studies I discuss or the studies they reference may be found to be flawed if examined in detail. If this is the case, it follows that my conclusions using these studies as premises would be flawed. However, the power of this article is not its qualitative analysis of every study; it is that it represents many of the major and most important publications on anabolic signaling mechanisms as well as the authors’ discussions of these studies.[/expand]